Forecasting temporal dynamics of cutaneous leishmaniasis in Northeast Brazil.

• Published in: PLoS Neglected Tropical Diseases
• Main Authors: Joseph A Lewnard, Lara Jirmanus, Nivison Nery Júnior, Paulo R Machado, Marshall J Glesby, Albert I Ko, Edgar M Carvalho, Albert Schriefer, Daniel M Weinberger
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2014
• Subjects: Arctic medicine. Tropical medicine; RC955-962; Public aspects of medicine; RA1-1270; Arctic
• Online Access: https://doi.org/10.1371/journal.pntd.0003283; https://doaj.org/article/1fd2f48acebc4274a786b7b5a46e5d26

INTRODUCTION:Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions. METHODOLOGY/PRINCIPAL FINDINGS:We fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation. SIGNIFICANCE:These outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets.